Distributed Observer-Based Cooperative Control Approach for Uncertain Nonlinear MASs Under Event-Triggered Communication

• Published in: IEEE transactions on automatic control Vol. 67; no. 5; pp. 2669 - 2676
• Main Authors: Deng, Chao, Wen, Changyun, Huang, Jiangshuai, Zhang, Xian-Ming, Zou, Ying
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Asymptotic properties; Closed loops; Cooperative control; Directed graphs; event-triggered communication; Feedback control; Laplace equations; Multi-agent systems; Multiagent systems; Nonlinear systems; Observers; Reference systems; Stability; Subsystems; time-varying tracking; Tracking errors; Tracking problem; Trajectory; uncertain nonlinear systems; Uncertain systems; Uncertainty
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2021.3090739

The distributed tracking problem for uncertain nonlinear multiagent systems (MASs) under event-triggered communication is an important issue. However, existing results provide solutions that can only ensure stability with bounded tracking errors, as asymptotic tracking is difficult to be achieved mainly due to the errors caused by event-triggering mechanisms and system uncertainties. In this article, with the aim of overcoming such difficulty, we propose a new methodology. The subsystems in MASs are divided into two groups, in which the first group consists of the subsystems that can access partial output of the reference system and the second one contains all the remaining subsystems. To estimate the state of the reference system, a new distributed event-triggered observer is first designed for the first group based on a combined output observable condition. Then, a distributed event-triggered observer is proposed for the second group by employing the observer state of the first group. Based on the designed observers, adaptive controllers are derived for all subsystems. It is established that global stability of the closed loop system is ensured and asymptotic convergence of all the tracking errors is achieved. Moreover, a simulation example is provided to show the effectiveness of the proposed method.